DocumentCode
2346937
Title
Two channels fuzzy c-means detection of multiple sclerosis lesions in multispectral MR images
Author
Ardizzone, E. ; Pirrone, R. ; Gambino, O. ; Peri, D.
Author_Institution
DIAI, Palermo Univ., Italy
Volume
2
fYear
2002
fDate
2002
Abstract
A novel approach to the detection of multiple sclerosis (MS) lesions in T2and PD-weighted MR images is presented. The core of the proposed method is the use of the two channels fuzzy c-means (FCM) segmentation of data, where the classical FCM approach runs, at first, on the two separate spectra. Then, the one-dimensional distributions of the cluster centers obtained by FCM, are composed in the two-dimensional one, which is a-priori imposed to the two-spectra segmentation procedure. Images are preprocessed to expand their grey level dynamics, and to allow clustering of noise and soft brain tissues. The description of the whole system is reported, along with several comparative experiments where a. pool of physicians judged the outcomes of the presented approach with the T2-only, the PD-only, and the standard two spectra FCM segmentation.
Keywords
biological tissues; brain; diseases; fuzzy set theory; image segmentation; medical image processing; pattern clustering; spectral analysis; MS lesions; PD-weighted MR images; T2-weighted MR images; fuzzy c-means detection; grey level dynamics; image preprocessing; multiple sclerosis lesions; multispectral MR images; noise clustering; soft brain tissues; two channels segmentation; two-spectra segmentation; Backpropagation; Biomedical imaging; Diseases; Image processing; Image segmentation; Lesions; Magnetic resonance imaging; Medical diagnosis; Multiple sclerosis; Noise level;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing. 2002. Proceedings. 2002 International Conference on
ISSN
1522-4880
Print_ISBN
0-7803-7622-6
Type
conf
DOI
10.1109/ICIP.2002.1039958
Filename
1039958
Link To Document